Probiotics Blunt the Anti-Hypertensive Effect of Blueberry Feeding in Hypertensive Rats without Altering Hippuric Acid Production
Bibliographic record
Abstract
Previously we showed that feeding polyphenol-rich wild blueberries to hypertensive rats lowered systolic blood pressure. Since probiotic bacteria produce bioactive metabolites from berry polyphenols that enhance the health benefits of berry consumption, we hypothesized that adding probiotics to a blueberry-enriched diet would augment the anti-hypertensive effects of blueberry consumption. Groups (n = 8) of male spontaneously hypertensive rats were fed one of four AIN '93G-based diets for 8 weeks: Control (CON); 3% freeze-dried wild blueberry (BB); 1% probiotic bacteria (PRO); or 3% BB + 1% PRO (BB+PRO). Blood pressure was measured at weeks 0, 2, 4, 6, and 8 by the tail-cuff method, and urine was collected at weeks 4 and 8 to determine markers of oxidative stress (F2-isoprostanes), nitric oxide synthesis (nitrites), and polyphenol metabolism (hippuric acid). Data were analyzed using mixed models ANOVA with repeated measures. Diet had a significant main effect on diastolic blood pressure (p = 0.046), with significantly lower measurements in the BB- vs. CON-fed rats (p = 0.035). Systolic blood pressure showed a similar but less pronounced response to diet (p = 0.220), again with the largest difference between the BB and CON groups. Absolute increase in blood pressure between weeks 0 and 8 tended to be smaller in the BB and PRO vs. CON and BB+PRO groups (systolic increase, p = 0.074; diastolic increase, p = 0.185). Diet had a significant main effect on hippuric acid excretion (p<0.0001), with 2- and ~1.5-fold higher levels at weeks 4 and 8, respectively, in the BB and BB+PRO vs. PRO and CON groups. Diet did not have a significant main effect on F2-isoprostane (p = 0.159) or nitrite excretion (p = 0.670). Our findings show that adding probiotics to a blueberry-enriched diet does not enhance and actually may impair the anti-hypertensive effect of blueberry consumption. However, probiotic bacteria are not interfering with blueberry polyphenol metabolism into hippuric acid.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".